Hello,
I simulated an ARMA 1,1 process and added a level shift. How can I get closer to the actual parameter estimates of the model if a shift is included?
Data A (Keep=x_int x t);
Retain e1 0 x1 0 x_int_1 500;
Do t=-100 To 10000;
e=Rannor(1);
x=(0.02+0.8*x1-0.4*e1+e); * create ARMA 1,1;
x_int=x_int_1+x; * integrate;
e1=e;
x1=x;
x_int_1=x_int;
If t>0 Then Output;
End;
Run;
Data A;
Set A;
dummy=IfN(t>=6000 & t<=7500,1,0);
x_int_d=x_int-dummy*200; * create shift;
Run;
ODS Graphics On;
Proc Timeseries Data=A Plot=Series;
Var x_int_d x_int;
Run;
ODS Graphics Off;
Proc Arima Data=A;
Title "Model 1: With shift";
Identify Var=x_int_d (1) CrossCorr=dummy;
Estimate p=1 q=1 Noint Input=dummy Method=ML;
Run;
Proc Arima Data=A;
Title "Model 2: No shift";
Identify Var=x_int (1);
Estimate p=1 q=1 Method=ML;
Run;
Thanks&kind regards
you have to diff the dummy too.
Proc Arima Data=A;
Title "Model 1: With shift";
Identify Var=x_int_d (1) CrossCorr=dummy(1);
Estimate p=1 q=1 Noint Input=dummy Method=ML;
Run;
you have to diff the dummy too.
Proc Arima Data=A;
Title "Model 1: With shift";
Identify Var=x_int_d (1) CrossCorr=dummy(1);
Estimate p=1 q=1 Noint Input=dummy Method=ML;
Run;
Join us for SAS Innovate April 16-19 at the Aria in Las Vegas. Bring the team and save big with our group pricing for a limited time only.
Pre-conference courses and tutorials are filling up fast and are always a sellout. Register today to reserve your seat.
Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.
Find more tutorials on the SAS Users YouTube channel.